AI 中文总结
研究针对高能物理中分析保存和可重复性难题，利用分析描述语言ADL及CutLang运行时解释器，以人类可读形式表达物理对象和标准，无需翻译。在ATLAS开放数据框架中重新实现基准分析，结果验证该工作流程可靠性，并评估CutLang能力及给出发展方向。
AI 中文摘要
分析描述语言（ADL）和CutLang运行时解释器为描述、执行和保存对撞机数据分析的物理内容提供了创新且可持续的解决方案。所有物理对象和事件选择标准都用ADL以人类可读形式表达，CutLang在运行时直接解释ADL描述而无需翻译成通用编程语言，产生可直接用于统计分析工具的事件选择。该方法通过将物理逻辑与特定实验软件基础设施解耦，解决了高能物理中分析保存和可重复性的长期挑战。本研究在ADL中重新实现了ATLAS开放数据C++框架内的几个基准分析，并使用13 TeV质心能量、对应10 fb$^{-1}$积分亮度的ATLAS开放数据提供的数据，通过CutLang执行。重新实现的分析结果与原始出版物高度一致，验证了ADL/CutLang工作流程是传统分析框架的可靠替代方案。该研究还详细评估了CutLang当前能力并确定了进一步发展的领域，为LHC社区更广泛采用基于ADL的分析保存提供了路线图。
英文摘要
Analysis Description Language (ADL) and the CutLang runtime interpreter offer an innovative and sustainable solution for describing, executing, and preserving the physics content of collider data analyses. In this solution, all physics objects and event selection criteria are expressed in a human-readable form using ADL, a domain-specific language designed for collider physics. ADL descriptions are interpreted directly at runtime by CutLang without translation into a general-purpose programming language, producing event selections that can be readily fed into statistical analysis tools. This approach addresses the long-standing challenge of analysis preservation and analysis reproducibility in high energy physics by decoupling the physics logic from experiment-specific software infrastructures. In this study, several benchmark analyses within ATLAS Open Data C++ Framework are reimplemented in ADL and executed with CutLang using data provided by ATLAS Open Data at a center-of-mass energy of 13 TeV and corresponding to an integrated luminosity of 10 fb$^{-1}$. The reimplemented analyses yield results in good agreement with the original publications, validating the ADL/CutLang workflow as a reliable alternative to traditional analysis frameworks. The study also provides a detailed assessment of CutLang's current capabilities and identifies areas for further development, offering a roadmap toward broader adoption of ADL-based analysis preservation in the LHC community.
